Proceedings of Seventh International Congress on Information and Communication Technology

Inhaltsverzeichnis

1. Frontmatter

2. Visualizing Student Engagement and Performance in Online Course: A Step to Smart Learning Environment

   Iman Al-Kindi, Zuhoor Al-Khanjari

   Abstract

   Students’ Engagement and Performance (EP) of online courses are analyzed and visualized in order to assist instructors in improving student’s performance at an early stage before the end of the academic semester. A fully online course for undergraduate students in the Department of Information Studies, College of Education, Sultan Qaboos University (SQU), was conducted. The total number of students in the course was 38. Students studied each course module and the instructor evaluated them based on a set of assessments. This paper explores the existence of possible relationships between student’s engagement and performance. In this paper, the authors only considered the results of the Mid Term Exam part. They extracted the necessary data for analysis purposes for the above-mentioned factors from the log file of the course. The results revealed promising relationships between the student’s engagement and performance. This indicates the importance of conducting this kind of case study as a step forward to achieve a smart learning environment.

3. IoT Automated Pill Dispenser for Elderly Care

   Saidatunnajwa Abdul Aziz, Aznida Abu Bakar Sajak, Ruwaida Ramly, Mohd Hanif Zulfakar

   Abstract

   This project is fabricated to ease medication consumption, especially for the elderly that always forget the proper time to consume their prescribed medicine. Thousands of cases have been recorded throughout the decade of wrong consumption of medicine. This may lead to serious issue as improper medicine dose is ineffective for the sickness that they suffer. This paper aims to develop an automated pill dispenser that triggers the alarm to the elderly, records the medication drop data using ThingSpeak, and notifies the caretaker through the Blynk application. This paper uses Arduino ATmega 2560 as the microcontroller for the device. It will be connected to a Wi-Fi module to transmit the data for the ThingSpeak platform and notifies the caretaker through the Blynk application. The paper will surely help eliminate the underdose and overdose issue, especially among the elderly and ease guardian’s worries about their absentness at the moment of medicine consumption. It is hoped that this paper can be used to replace hand-held pillbox device that is a hassle toward the elderly.

4. Android Malware Classification Addressing Repackaged Entities by the Evaluation of Static Features and Multiple Machine Learning Algorithms

   Md Rashedul Hasan

   Abstract

   Expanded usage and prevalence of android apps allows developers of malware to create new ways in various applications to unleash malware in various packaged types. This malware causes various leakage of information and a loss of revenue. In addition, the discovered software is repeatedly launched by unethical developers after classifying the program as malware. Unluckily, the program still remains undetected even after being repackaged. In this research, the topic of repackaging was discussed, emphasizing the implementation based on source code using the bag-of-words algorithm and testing the findings through machine learning. The findings of the assessment demonstrate comparatively improved result in this aspect than the existing implantation based on source code by adapting the bag-of-words strategy and implementing some supplementary dataset preprocessing. A vocabulary for identifying the malicious code has been developed in this study. Bag-of-words was used to classify malware trends using custom implementation. The findings were instantiated using various algorithms of machine learning. The concept was eventually implemented in a practical application too. The suggested method sets out a fairly new methodology for examining source code for android malware to tackle repackaging of malware.

5. Enterprise Architecture Quality Assessment

   Małgorzata Pańkowska

   Abstract

   The enterprise architecture (EA) assessment can be provided in different ways. In general, the EA assessment supports information communication technology (ICT) implementation. Beyond that, business organization stakeholders have an opportunity to monitor effectiveness and efficiency of business processes. They can modify the business structure, increase the business innovativeness, and ensure business strategy realization. Nowadays, EA stakeholders establish their own methodologies for EA quality assessment. This paper includes analyzes of the architecture frameworks, assessment models, and standards. This article aims to answer the question, if the design science research (DSR) paradigm is useful for EA quality assessment. Hence, this paper includes a proposal of new approach to EA quality assessment, based on emphasizing the relevance and rigor as key concepts.

6. Planning Rendezvous for Interplanetary Trajectories

   Aziz Anouar, Mohammed Bennani

   Abstract

   Great interests are always brought by the scientific community for the exploration of the solar system. Thus, important efforts are to be furnished to this goal. This paper aims to develop an approach of making rendezvous for the planets in the solar system as well as for a big asteroid. All the necessary equations are established by distinguishing the inside and the outside planets orbits relative to the earth. After that a simulation for the departure, the waiting time and the return trip are elaborated. This is followed obviously by an evaluation and comparison of the trip duration for each planet in the solar system. These simulation results would be without doubt very useful in the elaboration of the rendezvous planning strategies.

7. Peak Shaving in Microgrids Using Hybrid Storage

   Juraj Londák, Radoslav Vargic, Pavol Podhradský

   Abstract

   In this contribution, we focus on technical and economic aspects of using hybrid storage in microgrids for peak shaving. We perform feasibility analysis of hybrid storage consisting of conventional supercapacitors and chemical batteries. We use multiple real-life consumption profiles from various industry-oriented microgrids. The primary purpose is to construct digital twin model for reserved capacity simulation and prediction. The main objective is to find the equilibrium between technical innovations, acquisition costs, and energy cost savings.

8. A Machine Learning Approach to Predict SEER Cancer

   Dm. Mehedi Hasan Abid, Tariqul Islam, Zahura Zaman, Fahim Yusuf, Md. Assaduzzaman, Syed Akhter Hossain, Md. Ismail Jabiullah

   Abstract

   The SEER database is among the persuading stores regarding malignancy pointers inside us. The SEER list helps impact investigation for the gigantic measure of patients’ bolstered viewpoints for the most part ordered as an insightful segment and impact. Assistant careful proof nearly the carcinoma dataset is ordinarily started on the site of the National Cancer Institute. The main point of this work is that depending on the individual’s manifestations, and we will foresee whether individuals are in danger of malignant growth or not. Perseverance and desire for the benefit of malignant growth patients have the option to upsurge prophetic exactitude and limit in the end cause better-educated decisions. To the current end, various amendments smear AI to disease data of the surveillance, epidemiology, and end results database. It may be used to better forecast cancer in the medical sector, and these studies can give a good chance to enhance existing models and build new models for uncommon cancers of minority groups in particular. In this paper, the authors contribute to getting more predicted accuracy for SEER cancer and use it to better forecast cancer in the medical sector.

9. Digitization and Society: Forms of Interaction and Expression

   Valentina Milenkova, Boris Manov, Dobrinka Peicheva

   Abstract

   This article aims to reveal the digitalization as an integral part of the society. Every process, phenomenon, community and relationship is related to digitalization and information technology. This analysis presents different forms of symbiosis between society and digitalization. The objectives of the paper are to show specific dimensions of the advent of digitization and the various technologies in the Bulgarian society. The main research questions are related to the performance of high-tech level of Bulgarian online environment and focus on the main features of online learning, which are identified as new educational activities. Methodology of this article is based on results obtained from an online survey conducted in March 2021 with people of different ages, occupations and education. The survey questionnaire included topics that directly relate to the digitalization of society, the use of various digital devices and the Internet, participation in online education and attitudes toward it. The results obtained are indicators that digitalization of society is a real fact as well as that online learning has a place in the Bulgarian educational system. This article focuses on peoples' reactions, their assessments and views on ongoing online learning and its formatting. The whole article and the survey carried out are under the national project “Digital Media Literacy in the context of “Knowledge Society”: state and challenges”, № КП–06–H25/4, funded by National Science Fund—Bulgaria.

10. E-Managing the Pre-election Messages During the 2021 Parliamentary Campaigns in Bulgaria

    Neli Velinova, Mariyan Tomov, Lilia Raycheva, Lora Metanova

    Abstract

    The pre-election campaign for the early parliamentary vote in Bulgaria on July 11, 2021 was held in the conditions of an uncertain COVID-19 situation, political confrontation and the games of the European Football Championship. Following the trend of the previous regular elections of April 4 after which no government was appointed, Internet platforms and especially social networks have become increasingly popular channels for politicians to communicate with voters. The aim of the study focuses on the dynamics of pre-election online communication. The object is the specifics of the Internet connection between the audiences and the candidates for members of Parliament during the election campaign in July compared to the previous one in April. The subject refers to the digital election messages of the leaders of the political forces, presented in their Facebook profiles. The methodology is an empirical study and comparative analysis. The scope includes those political forces that have passed the 4% electoral threshold. The results are indicative for those interested in digital political communication during social isolation of pandemic.

11. Highly Stochastic Time Series Modeling using HTM in Comparison with Commonly Used Methods

    Filip Begiełło, Tomasz Bławucki

    Abstract

    This study compares the HTM models applicability in highly stochastic time series forecasting problems, to a range of commonly used approaches. The models were tested on a real-world data, representing raw material usage in a food processing company. The comparison was done on a set of 21 data series with a high disparity of underlying process characteristics. HTM models were evaluated against 6 other approaches. As a result, HTM models were able to outperform other models in 8 out of 21 cases, with an average improvement of around 20% of RMSE value, scoring in the first place as a most accurate approach.

12. Preliminary Results on Constraint Programming and Branch & Bound Algorithms for the Cyclic Bandwidth Sum Problem

    Valentina Narvaez-Teran, Eduardo Rodriguez-Tello, Frédéric Lardeux, Gabriel Ramírez-Torres

    Abstract

    The cyclic bandwidth sum problem (CBSP) consists in embedding a host graph into a cycle graph while minimizing the sum of cyclic distances between guest adjacent vertices embedded in the host. While the problem has been addressed by heuristic and metaheuristic methods, to the best of our knowledge, this is the first effort to apply exact methods. This work presents preliminary results on the use of constraint programming (CP) and a branch & bound (B &B) algorithm to solve the cyclic bandwidth sum problem in small graphs from commonly employed topologies. We created a CP model of the CBSP and devised two further refined versions by adding new constraints based in problem-specific knowledge. For our proposed B &B algorithm, we designed a custom criterion for search priority employing estimations of potential cost. The results provided an assessment of the pros and cons of both methodologies, with the CP approach offering a more reliable alternative in terms of solved instances, execution time, and implementation effort.

13. Analysis of Vulnerability Trends and Attacks in OT Systems

    Sandeep Gogineni Ravindrababu, Jim Alves-Foss

    Abstract

    For operational technology (OT) systems, security has been given an high priority in recent years after specific cyber-incidents targeting them. Earlier, these systems were focused mainly on reliability, and at present, security is also considered as an important factor to avoid production damage and financial losses. To improve the security in industrial systems, it is necessary to understand the flaws and provide countermeasures. In this paper, we focus on the cyber-incidents reported in Common Vulnerability Exposure (CVE) database on OT sub-systems like smart grids, Supervisory Control and Data Acquisition (SCADA) systems, embedded devices, and Programmable Logic Controllers (PLCs). We summarize the possible attacks on each of these sub-systems to gain broader insight of vulnerabilities present in them and use CVE database to enumerate trends.

14. Simulation Model of Respiratory Sound and Technology for Separating Characteristics of Pulmonary Disease

    Yiyang Luo, V. I. Lutsenko, S. M. Shulgar, Nguyen Xuan Anh

    Abstract

    In the process of human breathing, respiratory sounds are produced, and these sounds contain a lot of information related to the structure of the human airway. This paper uses computer and signal processing technology to collect and analyze the breath sounds to study the frequency spectrum difference between normal and abnormal respiratory sounds. Furthermore, it provides doctors/patients with a simple, quantitative, objective, intuitive, non-invasive auxiliary diagnosis tool for certain respiratory dysfunction diseases and respiratory physiology research methods.

15. Emergent Insight of the Cyber Security Management for Saudi Arabian Universities: A Content Analysis

    Hamzah Hadi Masmali, Shah J. Miah

    Abstract

    While cyber security has become a prominent concept of emerging information governance, the Kingdom of Saudi Arabia has been dealing with severe threats to individual and organizational IT systems for a long time. These risks have recently permeated into educational institutions, thereby undermining the confidentiality of information as well as the delivery of education. Recent research has identified various causes and possible solutions to the problem. However, most scholars have considered a reductionist approach, in which the ability of computer configurations to prevent unwanted intrusions is evaluated by breaking them down to their constituent parts. This method is inadequate at studying complex adaptive systems. Therefore, the proposed project is designed to utilize a holistic stance to assess the cybersecurity management and policies in Saudi Arabian universities. Qualitative research, entailing a thorough critical review of ten public universities, will be utilized to investigate the subject matter. The subsequent recommendations can be adopted to enhance the security of IT systems, not only in institutional settings but also in any other environment in which such structures are used.

16. Central Bank Digital Currencies (CBDCs) as a New Tool of E-Government: Socio-economic Impacts

    Galia Kondova, Patrik Rüegg

    Abstract

    A central bank digital currency (CBDC) in comparison with other forms of digital money presents a direct claim on the issuing central bank. There are three architecture types of CBDC, namely indirect CBDCs, hybrid CBDCs, and direct (retail) CBDCs, all based on blockchain technology. This paper briefly discusses these three types and outlines the major socio-economic effects this new e-government tool could have on the economy.

17. An Adaptive Self-modeling Network Model for Multilevel Organizational Learning

    Gülay Canbaloğlu, Jan Treur, Peter Roelofsma

    Abstract

    Multilevel organizational learning concerns an interplay of different types of learning at individual, team, and organizational levels. These processes use complex dynamic and adaptive mechanisms. A second-order adaptive network model for this is introduced here and illustrated.

18. A Novel Video Prediction Algorithm Based on Robust Spatiotemporal Convolutional Long Short-Term Memory (Robust-ST-ConvLSTM)

    Wael Saideni, David Helbert, Fabien Courreges, Jean Pierre Cances

    Abstract

    Recently, video prediction algorithms based on neural networks have become a promising research direction. Therefore, a new recurrent video prediction algorithm called “Robust Spatiotemporal Convolutional Long Short-Term Memory” (Robust-ST-ConvLSTM) is proposed in this paper. Robust-ST-ConvLSTM proposes a new internal mechanism that is able to regulate efficiently the flow of spatiotemporal information from video signals based on higher-order Convolutional-LSTM. The spatiotemporal information is carried through the entire network to optimize and control the prediction potential of the ConvLSTM cell. In addition, in traditional ConvLSTM units, cell states, that carry relevant information throughout the processing of the input sequence, are updated using only one previous hidden state, which holds information on previous data unit already seen by the network. However, our Robust-ST-ConvLSTM unit will rely on N previous hidden states, that provide temporal context for the motion in video scenes, in the cell state updating process. Experimental results further suggest that the proposed architecture can improve the state-of-the-art video prediction methods significantly on two challenging datasets, including the standard Moving MNIST dataset, and the commonly used video prediction KTH dataset, as human motion dataset.